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1.
J Sci Med Sport ; 25(10): 850-854, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-1926705

ABSTRACT

OBJECTIVES: Describe the highest frequency and variability for tackle events in rugby league. Investigate seasonal differences in total tackle events per match over a seven-year period. DESIGN: Retrospective observational. METHODS: Tackle events (i.e., ball carrier events [attacker] and tackler involvements [defender]) from 864 male professional rugby league players competing in 1176 Super League matches from 2014 to 2020 were included. A series of linear mixed effect models were used to determine the frequency and variability during peak 1-, 3-, 5-, 10-, 20-, 40-min and whole-match tackle events per player per match at a positional group level. Differences between seasons for the total number of tackle events per match were compared using a one-way analysis of variance and with Tukey's honestly significant difference test. RESULTS: Tackle events were greatest for Props (51.5 [47.7-55.4] per match). Within-players, between-matches, and between-seasons variability was <10 % for tackle events. There were significantly less tackle events and tackler involvements per match in 2014 and a significantly more tackle events per match in season 2020b when compared with all other seasons. CONCLUSIONS: Large between-position variability in peak tackle events, ball carrier events, and tackler involvements would suggest that coaches should separate players into positional groups and prescribe training accordingly. Total number of tackle events, ball carrier events, and tackler involvements were significantly greater in season 2020b when compared to season 2014 to 2019 (inclusive) which may be a consequence of rule changes introduced to the sport.


Subject(s)
Athletic Performance , Football , Humans , Linear Models , Male , Retrospective Studies , Rugby
2.
Int J Environ Res Public Health ; 18(22)2021 11 21.
Article in English | MEDLINE | ID: covidwho-1524013

ABSTRACT

The COVID-19 pandemic interrupted professional football in the 2019/2020 season, and football experts anticipate that the consequences of lockdown measures will negatively affect the physical performance of players once competition restarts. This study aimed to evaluate position-specific match running performance (MRP) to determine the effect of COVID-19 lockdowns on the physical performance of professional football players. Players' MRPs (n = 124) were observed in matches before and after the COVID-19 lockdown in the 2019/2020 season of the highest level of national competition in Croatia and were classified according to player position: central defenders (CD; n = 42), fullbacks (FB; n = 20), midfielders (MF; n = 46), and forwards (FW; n = 16). The MRPs were measured using Global Positioning System, and included the total distance covered, low-intensity running (≤14.3 km/h), running (14.4-19.7 km/h), high-intensity running (≥19.8 km/h), total accelerations (>0.5 m/s2), high-intensity accelerations (>3 m/s2), total decelerations (less than -0.5 m/s2), and high-intensity decelerations (less than -3 m/s2). The results indicated that, in matches after the COVID-19 lockdown, (i) CDs and FBs featured lower running and high-intensity running (t-value: from 2.05 to 3.51; all p < 0.05; moderate to large effect sizes), (ii) MFs covered a greater distance in low-intensity running and achieved a lower number of total accelerations, and total and high-intensity decelerations (t-value: from -3.54 to 2.46; all p < 0.05, moderate to large effect sizes), and (iii) FWs featured lower high-intensity running (t-value = 2.66, p = 0.02, large effect size). These findings demonstrate that the physical performances of football players from the Croatian first division significantly decreased in matches after the COVID-19 lockdown. A combination of inadequate adaptation to football-specific match demands and a crowded schedule after the competition was restarted most likely resulted in such an effect.


Subject(s)
Athletic Performance , COVID-19 , Football , Running , Soccer , Communicable Disease Control , Geographic Information Systems , Humans , Pandemics , SARS-CoV-2
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